What is Swarm Intelligence?
First introduced by Gerardo Beni and Jing Wang in 1989, swarm intelligence is the collective behavior of decentralized, self-organized systems, for which social insects are one of the best examples.
Swarm intelligence is an attempt to design algorithms or distributed problem-solving devices intended to mimic the collective behavior of social insect colonies.
Essentially, swarm intelligence improves our collective behaviors (our outputs).
Derek and Laura Cabrera, systems theorists and professors at Cornell University compare this to a game of chess in Flock Not Clock,
“The game of chess has simple enough rules for a child to master, yet there are 318 billion possible ways to play the first four moves. The behaviors (or outputs) of systems – be they a flock of starlings or biodiversity writ large, chess matches or organizations – are emergent properties of simple rules at the local level. By identifying, understanding, and applying these simple rules, we can make the outputs better.”
Let’s look at an example of how these simple rules work for an ant colony:
Simple rules outlined by the Cabrera’s allow social insects (such as ants) to become a superorganism. These simple rules are as follows:
- Look for food. Ants randomly forage for food.
- If you find food, shoot pheromones. A few find food and communicate by leaving a pheromone trail increasing probability of collective action on food piles.
- Never cross a pheromone trail. Self-organizing behavior around simple rules produces collective intelligence.
How to identify simple rules that work
The Cabrera’s have defined four simple and deeply connected rules that apply in all types of organizations: Vision (V), Mission (M), Capacity (C), Learning (L).
- Vision (V): Your desired future state or goal (what do you see?). For example, ask the following: What do you see today? What should you see tomorrow?
- Mission (M): Repeatable actions that bring out the vision (what do you do?).
- Capacity (C): Systems that provide readiness to execute the mission (how do we align capacity?). Here you build capacity to do the mission.
- Learning (L): Continuous improvement of systems of capacity based on feedback from the external environment (love of learning). For example, the Cabrera’s explain that a big part of learning is making people aware of the lens through which they perceive reality.